Abstract

We study models and algorithms for Programmable Matter (PM), that is matter with the ability to change its physical properties (e.g., shape or optical properties) in a programmable fashion. PM can be implemented by assembling a system of weak self-organizing computational elements, called particles, that can be programmed via distributed algorithms to collectively achieve some global task. Recent advances in the production of nanotechnologies have rendered such systems increasingly possible in practice, thus triggering research interests from many areas of computer science. The most established models for PM assume that particles: are modeled as finite state automata; are all identical, executing the same algorithm based on local observation of the surroundings; live and operate in the cells of a hexagonal grid; can move from one cell to another by repeatedly alternating between a contracted state (a particle occupies one cell) and an expanded state (a particle occupies two neighboring cells). Given these elementary features, it is rather hard to design distributed algorithms even for basic tasks and, in fact, all existing solutions to solve fundamental problems via PM have resorted to endowing PM systems with various capabilities to overcome such hardness, thus assuming quite unrealistic features. In this paper, we move toward more realistic computational models for PM. Specifically, we first introduce SILBOT, a new modeling approach that relaxes several assumptions used in previous ones. Second, we present a distributed algorithm to solve, in the SILBOT model, a foundational primitive for PM, namely Leader Election. This algorithm works in O(n) rounds for all initial configurations of n particles that are both connected (i.e. particles induce a connected graph) and compact (i.e. without holes, that is no empty cells surrounded by particles occur). As usual in asynchronous contexts, a round is intended as the time within which all particles have been activated at least once. Third, we show that, if the initial configuration admits holes, it is impossible to achieve leader election while preserving connectivity. Finally, by slightly empowering the robots, we design an algorithm to handle initial configurations admitting holes that in O(n <sup xmlns:mml="http://www.w3.org/1998/Math/MathML" xmlns:xlink="http://www.w3.org/1999/xlink">2</sup> ) rounds solves the leader election problem while obtaining also compaction.

Highlights

  • The term Programmable Matter (PM, shortly) was first coined in a seminal work by Toffoli et al [37] and, since the beginning, it has been used to denote systems of weak and small computational elements, called particles, that can be programmed via distributed algorithms to VOLUME 8, 2020

  • This paper explores theoretical issues related to the modeling and algorithm design for PM, we move a step closer to practically implementable programmable matter

  • As previously remarked, less computational power usually lead to harder algorithm design and even impossibility results for basic tasks [20]. We show that this is not the case, since the SILBOT model is powerful enough to allow the resolution of various problems that are relevant in the context of PM

Read more

Summary

INTRODUCTION

Matter having the ability to change its physical properties (e.g., shape, optical properties, etc.) in a programmable fashion has been recently the subject of many studies in many. Among them perhaps the most promising (in terms of quality of the abstraction, as well documented in the literature [13], [20]) is the so-called geometric Amoebot model [19], which is inspired by the behavior of the amoeba Such a model, as well as other prominent ones, considers a swarm of decentralized autonomous self-organizing particles that: i) are modeled as finite state automata; ii) are all identical, executing the same algorithm based on local observation of the surroundings; iii) are displaced in the cells of a hexagonal grid (represented by a triangular lattice); iv) can move from cell to cell by repeatedly alternating between two states, namely contracted (a particle occupies one cell) and expanded (the particle occupies two neighboring cells). We formally prove that all our algorithms are correct: starting from an arbitrary initial connected configuration (either connected or not), we show that in the system there are at most three particles elected as leader

THE SILBOT MODEL
ARBITRARY CONNECTED CONFIGURATIONS
COMPACTION AND ELECTION
CONCLUSION AND EXTENSIONS
Full Text
Published version (Free)

Talk to us

Join us for a 30 min session where you can share your feedback and ask us any queries you have

Schedule a call